Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

An optimization model for scheduling the efficient flow of waste material in an underground gold mine

In an underground gold mine, the movement of ore and waste material occurs on a massive scale and short-term excavation activities should be scheduled so that that the right proportions of these materials are moving through the mine in order to meet production targets. In the proposed project, a mathematical optimization model will be formulated and tested on-site, in order to improve the short-term excavation scheduling activities, resulting in the desired balance of ore and waste material flowing through the mine. This model is to be used by GoldCorp managers as a decision support tool in order to ensure that the efficiency of scheduled operations are optimized. The intern funded by this project will be a highly qualified person, capable of making a major contribution to Canada’s international competiveness in the mining industry.

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Faculty Supervisor:

Kevin Crowe

Student:

Suliman Emdini Gliwan

Partner:

Newmont Goldcorp

Discipline:

Resources and environmental management

Sector:

Mining and quarrying

University:

Lakehead University

Program:

Accelerate

The Investigation of a Low Temperature Co-Fired Ceramic (LTCC) Fabrication Process for the Design of Advanced Millimeter-Wave Components for 5G Communication Technology

The main objective of this project is to design and test millimeter-wave RF front end components for applications in 5G new radio communication systems utilizing the thin-film multilayer LTCC fabrication process developed at ACAMP. With these fabricated and characterized prototypes, ACAMP will be able to showcase its specialized LTCC fabrication process and provide support to potential Canadian technology clients and companies looking to develop technology for the upcoming 5G mobile communications market. The project will provide the intern an opportunity to gain knowledge in the design and testing of millimeter-wave antennas and filters for advanced communication systems, as well as to network and develop contacts through ACAMP’s clients within the 5G mobile communications industry.

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Faculty Supervisor:

Mojgan Daneshmand

Student:

Amarveer Dhillon;Zahra Abbasi;Eric Der

Partner:

Alberta Centre for Advanced MNT Products

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Alberta

Program:

Accelerate

A flexible non-enzymatic lactate sensor with long shelf life to detect anastomotic leaks post-surgery

Development of leaks in abdominal cavity following surgery cause acute complications that have a high mortality rate and lead to expensive corrective procedures. These leaks are mostly detected following the development of complications as currently there is no method for their early detection and hence timely intervention which can save lives is not possible. In this aspect, lactate is a crucial bio-marker that is excreted from the leak site prior to the development of a full breach and hence its monitoring will lead to early detection of such leaks. Under this project a lactate sensor will be developed that can be integrated with a catheter that has been developed by NERv technologies for monitoring of such leaks in the abdominal cavity following a surgical procedure. The developed lactate sensor will hence be a crucial component for monitoring the post-operative health of the patient and timely detection of such leaks. The development of this sensor will significantly enhance the ability of catheter made by NERv towards monitoring of such post-operative applications. The developed technology will also lead to filing of patent and hence contribute to the Canadian economy.

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Faculty Supervisor:

Vivek Maheshwari

Student:

Mohamed Okasha

Partner:

NERV TECHNOLOGY Inc

Discipline:

Chemistry

Sector:

Life sciences

University:

University of Waterloo

Program:

Accelerate

Catalyst Optimization for Solar-Driven GHG Conversion to Fuels

The anthropogenic emissions of the greenhouse gases carbon dioxide and methane are the leading cause of global climate change. Furthermore, these emissions are related to the manufacture of fuels and carbon-based products. Solar fuels technology addresses both of these issues. Photocatalysts, nanomaterials engineering to directly use solar energy, can convert carbon dioxide and methane into the same carbon-based consumer products we rely on every day using sunlight. This technology represents an advancement toward a clean and carbon recycling economy.

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Faculty Supervisor:

Geoffrey Ozin;Mohini Sain;Robert A. Batey

Student:

Alexandra Tavasoli;Thomas Wood

Partner:

Solistra

Discipline:

Chemistry

Sector:

University:

University of Toronto

Program:

Accelerate

Automated Diagnostic System for Remote Monitoring of a Concrete Dam

Structural Health Monitoring (SHM) has tremendous potential to detect incipient structural failures in various components, e.g., onset of fatigue damage, corrosion, spalling and delamination in the structures during their service life, so that preventive actions can be employed in a timely manner. St. Clair Region Conservation Authority (SCRCA) has felt immediate need for real-time monitoring of W. Darcy McKeough Floodway, one of the flood control dams that has been subjected to fluctuating operational conditions, adverse weather and climate change over many years. The dam is consisted of an earth fill embankment, concrete control structure housing two sluice gates and a diversion channel. Real-time detailed monitoring of the embankment, sluice gates and diversion channel is of paramount importance to avoid water seepage and future flooding issues. Main objective of this project is to develop automated diagnostic system for remote inspection of the concrete dam by harnessing machine learning techniques.

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Faculty Supervisor:

Ayan Sadhu

Student:

Mohamed Barbosh

Partner:

St. Clair Region Conservation Authority

Discipline:

Engineering - civil

Sector:

Construction and infrastructure

University:

Western University

Program:

Accelerate

Rural community sustainability research program at the Applied Research and Innovation Center – Selkirk College

This proposed rural community sustainability research program at the Rural Development Institute (RDI) aims to collectively address and support rural issues through research. The main themes surround sustainable economic development and diversification, climate resiliency, environmental protection, and sustainable community indicators for development and prosperity. Economic development and diversification will entail collaboration between different scales of human organization and stakeholders concerning economic projections, and models to help combat future rural community issues. In addition, applied rural climate adaptation and response may include smaller projects that define community-based strategies, expectations, and required supports in adapting to climate change. Throughout all of these themes, the need for a collective approach and collaborative research in the rural region of the Columbia Basin can be identified. The aim of this research initiative is to create a research program that provides the tools, skills, individuals, and resources required to support these themes for sustainable local communities.

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Faculty Supervisor:

Adela Tesarek Kincaid

Student:

Kayla Tillapaugh

Partner:

Discipline:

Other

Sector:

University:

Selkirk College

Program:

Accelerate

Automatic weld seam positioning on sheet metal enclosures by semi-supervised deep learning

Deep learning in computer vision has set new standards in mobile and web-based applications. The power of learning-based computer vision has also tremendous potential in machine vision. Traditionally, machine vision in manufacturing employs analytic solutions often resulting in excellent accuracy but poor robustness. The goal of this project is to increase robustness of a vision-based measurement process in sheet metal manufacturing using deep learning. The ability to accommodate variations in manufacturing enables a manufacturer to provide customized solutions in a more time efficient and cost effective way. One of the major challenges in machine vision is the lack of appropriate large-size training data for supervised learning. This project will train a deep learning algorithm based on all kind of data including expert-labelled images, existing results of a machine vision algorithm and unlabeled images. The project is to provide an effective solution for the industrial partner and general research results.

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Faculty Supervisor:

Jochen Lang

Student:

Wenbin Zhang

Partner:

Enclosures Direct Inc

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Ottawa

Program:

Accelerate

Morphological investigation of adhesive blends and its effect on multilayer coating performance

In the pipeline industry, the heat shrink sleeves (HSS) are the protective layer usually composed of two layers, namely, an adhesive layer and a crosslinked backing layer such as polypropylene (PP) or polyethylene (PE). In order to maintain the desired properties of HSS, each of the layers must maintain their properties during processing, storage, and installation. In partnership with Canusa-CPS, the proposed research aims at addressing the relationships between the morphological structure and interfacial strength of the adhesive layers with their performance. Combining the characterization, rheological and mechanical analysis, the proposed study will correlate the mechanical performance of the adhesives to their material, design and morphological parameters. The research will be beneficial to our partner in developing a new generation of adhesives.

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Faculty Supervisor:

Ehsan Behzadfar

Student:

Farzad Gholami

Partner:

Canusa-CPS

Discipline:

Engineering - chemical / biological

Sector:

Manufacturing

University:

Lakehead University

Program:

Accelerate

Development of an Extensible Framework for Assessing Digital Health Innovation Hubs (DHI-HUB)

New information technologies are becoming an important part of the health care system. A priority both provincially and nationally is the establishment of an enhanced network of general practitioners using the latest information technologies to acquire, store and use patient information. This will involve deployment of person-centred digitally-enabled information technologies in a new structure known as Digital Health Innovation HUBs (DHI-HUBs). The hubs will provide an opportunity to test innovative health technologies in health care. In this project, we will develop a framework for evaluating the effectiveness and outcomes of DHI-HUBs. The research methods will include ideas from implementation science, health IT project management and the emerging field of health informatics. The approach to evaluation of an implementation of a set of innovative health technologies will be applied in the Okanagan region of Canada and will be designed to be generalizable to other health regions.

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Faculty Supervisor:

Elizabeth Borycki;Andre Kushniruk;Helen Monkman

Student:

Angela Espejo

Partner:

Telus

Discipline:

Other

Sector:

Information and communications technologies

University:

University of Victoria

Program:

Accelerate

Do existing lending products of credit unions meet the financing needs of co-operatives – The case of Libro Credit Union and Ontario’s Co-operative Sector

Credit unions and co-operatives share a common identity and foundational values as organizations that meet the economic, social, and cultural needs of their member-owners. A perennial concern for the credit union and co-operative sectors has been the need to identify opportunities for collaboration to advance the prominence of member-owned models. This research surveys and interviews co-operatives in Southwestern Ontario to understand their financing needs, and to identify why existing financial products do not meet these needs. The researchers will facilitate a focus group with Libro Credit Union staff to reflect on the survey and interview findings with the goal of identifying opportunities for new lending products that meet the needs of both credit unions and co-operat

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Faculty Supervisor:

Sean Geobey

Student:

Sean Campbell

Partner:

Libro Credit Union

Discipline:

Environmental sciences

Sector:

University:

University of Waterloo

Program:

Accelerate

Transitioning to adulthood: Implementing a modified CO-OP approach to improve the occupational performance of youth with Autism Spectrum Disorder (ASD)

There is a current lack of evidence-based, client-centred interventions to support youth with ASD in developing their life skills necessary for their successful transition to adulthood. The Cognitive Orientation to Daily Occupational Performance (CO-OP) approach is a client-centred, meta-cognitive intervention that supports skill acquisition through the use of global and domain specific cognitive strategies. Preliminary research has shown the promise of using the CO-OP approach with youth with ASD in achieving motor-based, social and organizational goals. The purpose of this study evaluate if the CO-OP approach delivered in a group format, is successful in supporting youth with ASD improve their independence and performance of their chosen life skill goals. This study will lay a foundation to support the development of an evidence-based intervention approach when working with youth with ASD focused on developing life skills necessary for their successful transition to adulthood.

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Faculty Supervisor:

Jessie Wilson;Angela Mandich

Student:

Richa Mehta

Partner:

CBI Health Group

Discipline:

Kinesiology

Sector:

Health care and social assistance

University:

Western University

Program:

Accelerate

Water-based binders for the 3D printing and sintering of metals

Rapidia has developed a water-based approach to metal 3D printing that is faster, simpler, and more cost effective than the current systems on the market. This novel approach enables printed parts to be sintered directly, eliminating the time- and chemically- intensive intermediate de-binding step required for other processes. In order to implement this technique, the formulation of the initial paste used for printing is an essential component to optimize. We will be studying how the chemical composition of the paste formulation impacts its performance in the printing and sintering steps, with the ultimate goal of developing advanced formulations to optimize the quality of the final metal parts. This research project could significantly advance Rapidia’s technology, accelerate their growth in the industry, and stimulate the Canadian economy.

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Faculty Supervisor:

Mark MacLachlan

Student:

David Ester

Partner:

Rapidia Tech Inc

Discipline:

Chemistry

Sector:

Manufacturing

University:

University of British Columbia

Program:

Accelerate

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